Ice Dogs | |
GP: 0 | W: 0 | L: 0 GF: 0 | GA: 0 | PP%: 0% | PK%: 0% GM : Daniel Pigeon | Morale : 40 | Team Overall : 63 |
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Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
# | Player Name | C | L | R | D | CON | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | OV | TA | SP | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | Paul Byron | X | 100.00 | 86 | 50 | 90 | 75 | 50 | 60 | 55 | 57 | 55 | 52 | 64 | 68 | 53 | 89 | 67 | 0 | 40 | 69 | 0 | 34 | 2 | 4,000,000$ | ||||
2 | Lane Pederson | X | 100.00 | 89 | 65 | 75 | 73 | 66 | 77 | 42 | 63 | 65 | 57 | 66 | 59 | 55 | 64 | 65 | 0 | 40 | 68 | 0 | 26 | 1 | 735,000$ | ||||
3 | Jasper Weatherby | X | 100.00 | 69 | 52 | 88 | 73 | 83 | 60 | 55 | 62 | 64 | 53 | 61 | 58 | 49 | 58 | 61 | 0 | 40 | 66 | 0 | 25 | 1 | 842,500$ | ||||
4 | Alexander Steen | X | 100.00 | 47 | 45 | 55 | 80 | 69 | 60 | 55 | 64 | 39 | 58 | 53 | 55 | 30 | 52 | 75 | 0 | 40 | 64 | 0 | 39 | 3 | 3,500,000$ | ||||
5 | Garrett Pilon | X | 100.00 | 54 | 50 | 90 | 73 | 65 | 60 | 55 | 55 | 56 | 50 | 65 | 50 | 36 | 60 | 62 | 0 | 40 | 63 | 0 | 25 | 2 | 750,000$ | ||||
6 | Brendan Perlini | X | 100.00 | 61 | 51 | 88 | 73 | 78 | 60 | 55 | 55 | 45 | 50 | 58 | 50 | 44 | 70 | 57 | 0 | 40 | 62 | 0 | 27 | 5 | 750,000$ | ||||
7 | Mikhail Grigorenko | X | 100.00 | 47 | 45 | 55 | 73 | 77 | 60 | 55 | 59 | 34 | 54 | 51 | 52 | 30 | 52 | 65 | 0 | 40 | 61 | 0 | 29 | 3 | 1,200,000$ | ||||
8 | Kole Sherwood | X | 100.00 | 77 | 50 | 90 | 73 | 72 | 60 | 55 | 55 | 32 | 50 | 50 | 50 | 30 | 65 | 52 | 0 | 40 | 61 | 0 | 26 | 1 | 735,000$ | ||||
9 | Markus Hannikainen | X | 100.00 | 47 | 45 | 55 | 73 | 70 | 60 | 55 | 59 | 35 | 55 | 51 | 52 | 30 | 52 | 66 | 0 | 40 | 60 | 0 | 30 | 2 | 750,000$ | ||||
10 | Arnaud Durandeau (R) | X | 100.00 | 54 | 50 | 76 | 67 | 64 | 78 | 30 | 56 | 36 | 50 | 50 | 54 | 31 | 58 | 55 | 0 | 40 | 60 | N | 0 | 24 | 5 | 750,000$ | |||
11 | Sean Malone | X | 100.00 | 47 | 45 | 55 | 73 | 66 | 60 | 55 | 59 | 33 | 54 | 50 | 52 | 30 | 52 | 64 | 0 | 40 | 60 | 0 | 28 | 4 | 750,000$ | ||||
12 | Markus Granlund | X | 100.00 | 47 | 45 | 55 | 73 | 63 | 60 | 55 | 59 | 35 | 55 | 51 | 52 | 30 | 52 | 66 | 0 | 40 | 60 | 0 | 30 | 2 | 1,300,000$ | ||||
13 | Zachary Senyshyn | X | 100.00 | 66 | 50 | 63 | 73 | 71 | 60 | 55 | 55 | 31 | 50 | 50 | 50 | 30 | 65 | 51 | 0 | 40 | 59 | 0 | 26 | 1 | 700,000$ | ||||
14 | Jayce Hawryluk | X | 100.00 | 47 | 45 | 55 | 73 | 63 | 60 | 55 | 58 | 33 | 54 | 50 | 51 | 30 | 52 | 63 | 0 | 40 | 59 | 0 | 27 | 5 | 750,000$ | ||||
15 | Andrej Sekera | X | 100.00 | 59 | 52 | 85 | 75 | 67 | 60 | 55 | 55 | 35 | 54 | 57 | 61 | 48 | 99 | 66 | 0 | 40 | 67 | 0 | 37 | 2 | 4,500,000$ | ||||
16 | Jacob Bernard-Docker | X | 100.00 | 63 | 59 | 79 | 72 | 66 | 76 | 37 | 55 | 40 | 55 | 51 | 64 | 33 | 61 | 58 | 0 | 40 | 66 | 0 | 23 | 1 | 925,000$ | ||||
17 | Ronnie Attard | X | 100.00 | 62 | 50 | 90 | 67 | 78 | 82 | 30 | 60 | 36 | 50 | 50 | 66 | 30 | 60 | 56 | 0 | 40 | 66 | 0 | 24 | 1 | 842,500$ | ||||
18 | Slater Koekkoek | X | 100.00 | 69 | 52 | 78 | 73 | 72 | 60 | 55 | 55 | 35 | 61 | 50 | 58 | 45 | 76 | 63 | 0 | 40 | 66 | 0 | 29 | 3 | 850,000$ | ||||
19 | Jay Bouwmeester | X | 100.00 | 47 | 45 | 55 | 80 | 80 | 60 | 55 | 65 | 39 | 58 | 53 | 55 | 30 | 52 | 76 | 0 | 40 | 65 | 0 | 40 | 2 | 3,250,000$ | ||||
20 | Mac Hollowell (R) | X | 100.00 | 50 | 50 | 81 | 72 | 52 | 78 | 30 | 55 | 36 | 64 | 50 | 59 | 31 | 59 | 63 | 0 | 40 | 63 | 0 | 25 | 2 | 750,000$ | ||||
21 | Niklas Hjalmarsson | X | 100.00 | 47 | 45 | 55 | 71 | 75 | 60 | 55 | 63 | 37 | 57 | 52 | 54 | 30 | 52 | 72 | 0 | 40 | 63 | 0 | 36 | 2 | 6,000,000$ | ||||
22 | Aaron Ness | X | 100.00 | 47 | 45 | 55 | 73 | 58 | 60 | 55 | 61 | 36 | 56 | 51 | 53 | 30 | 52 | 69 | 0 | 40 | 61 | 0 | 33 | 2 | 650,000$ | ||||
23 | Nelson Nogier | X | 100.00 | 47 | 45 | 55 | 73 | 71 | 60 | 55 | 58 | 33 | 54 | 50 | 51 | 30 | 52 | 63 | 0 | 40 | 60 | 0 | 27 | 5 | 750,000$ | ||||
24 | Ryan Murphy | X | 100.00 | 47 | 45 | 55 | 73 | 61 | 60 | 55 | 59 | 35 | 55 | 51 | 52 | 30 | 52 | 66 | 0 | 40 | 60 | 0 | 30 | 2 | 825,000$ | ||||
Scratches | |||||||||||||||||||||||||||||
1 | Cameron Hillis | X | 100.00 | 42 | 50 | 90 | 73 | 53 | 60 | 55 | 55 | 42 | 50 | 50 | 50 | 30 | 56 | 51 | 0 | 65 | 57 | 0 | 23 | 1 | 842,500$ | ||||
TEAM AVERAGE | 100.00 | 57 | 49 | 71 | 73 | 68 | 64 | 51 | 58 | 40 | 54 | 53 | 55 | 35 | 60 | 63 | 0 | 41 | 63 |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
# | Goalie Name | CON | SK | DU | EN | SZ | AG | RB | SC | HS | RT | PH | PS | EX | LD | PO | MO | OV | TA | SP | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | Joseph Woll | 100.00 | 70 | 44 | 92 | 83 | 82 | 59 | 65 | 66 | 65 | 75 | 54 | 59 | 64 | 0 | 40 | 69 | 0 | 25 | 2 | 750,000$ | |
Scratches | |||||||||||||||||||||||
TEAM AVERAGE | 100.00 | 70 | 44 | 92 | 83 | 82 | 59 | 65 | 66 | 65 | 75 | 54 | 59 | 64 | 0 | 40 | 69 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
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Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
# | Player Name | Team Name | POS | GP | G | A | P | +/- | PIM | PIM5 | HIT | HTT | SHT | OSB | OSM | SHT% | SB | MP | AMG | PPG | PPA | PPP | PPS | PPM | PKG | PKA | PKP | PKS | PKM | GW | GT | FO% | FOT | GA | TA | EG | HT | P/20 | PSG | PSS | FW | FL | FT | S1 | S2 | S3 |
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Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
# | Goalie Name | Team Name | GP | W | L | OTL | PCT | GAA | MP | PIM | SO | GA | SA | SAR | A | EG | PS % | PSA | ST | BG | S1 | S2 | S3 |
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Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Player Name | Team Name | POS | Age | Birthday | Rookie | Weight | Height | No Trade | Available For Trade | Acquired By | Last Trade Date | Force Waivers | Waiver Possible | Contract | Contrat Signature Date | Type | Current Salary | Salary Remaining | Salary Cap | Salary Cap Remaining | Exclude from Salary Cap | Salary Year 2 | Salary Year 3 | Salary Year 4 | Salary Year 5 | Salary Year 6 | Salary Year 7 | Salary Year 8 | Salary Year 9 | Salary Year 10 | No Trade Year 2 | No Trade Year 3 | No Trade Year 4 | No Trade Year 5 | No Trade Year 6 | No Trade Year 7 | No Trade Year 8 | No Trade Year 9 | No Trade Year 10 | Link |
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Aaron Ness | Ice Dogs (DAY) | D | 33 | 1990-05-18 | No | 184 Lbs | 5 ft10 | No | No | N/A | No | No | 2 | Pro & Farm | 650,000$ | 650,000$ | 0$ | 0$ | No | 650,000$ | - | - | - | - | - | - | - | - | No | - | - | - | - | - | - | - | - | |||
Alexander Steen | Ice Dogs (DAY) | LW | 39 | 1984-03-01 | No | 211 Lbs | 6 ft0 | No | No | N/A | No | No | 3 | Pro & Farm | 3,500,000$ | 3,500,000$ | 0$ | 0$ | No | 3,500,000$ | 3,500,000$ | - | - | - | - | - | - | - | No | No | - | - | - | - | - | - | - | |||
Andrej Sekera | Ice Dogs (DAY) | D | 37 | 1986-06-08 | No | 200 Lbs | 6 ft0 | No | No | N/A | No | No | 2 | Pro & Farm | 4,500,000$ | 4,500,000$ | 0$ | 0$ | No | 4,500,000$ | - | - | - | - | - | - | - | - | No | - | - | - | - | - | - | - | - | |||
Arnaud Durandeau | Ice Dogs (DAY) | LW | 24 | 1999-01-14 | Yes | 185 Lbs | 6 ft0 | Yes | No | N/A | No | No | 5 | Pro & Farm | 750,000$ | 750,000$ | 0$ | 0$ | No | 750,000$ | 750,000$ | 750,000$ | 750,000$ | - | - | - | - | - | Yes | Yes | Yes | Yes | - | - | - | - | - | |||
Brendan Perlini | Ice Dogs (DAY) | LW | 27 | 1996-04-27 | No | 211 Lbs | 6 ft3 | No | No | N/A | No | No | 5 | Pro & Farm | 750,000$ | 750,000$ | 0$ | 0$ | No | 750,000$ | 750,000$ | 750,000$ | 750,000$ | - | - | - | - | - | No | No | No | No | - | - | - | - | - | |||
Cameron Hillis | Ice Dogs (DAY) | C | 23 | 2000-06-24 | No | 175 Lbs | 5 ft9 | No | No | N/A | No | No | 1 | Pro & Farm | 842,500$ | 842,500$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |||
Garrett Pilon | Ice Dogs (DAY) | C | 25 | 1998-04-13 | No | 191 Lbs | 6 ft0 | No | No | N/A | No | No | 2 | Pro & Farm | 750,000$ | 750,000$ | 0$ | 0$ | No | 750,000$ | - | - | - | - | - | - | - | - | No | - | - | - | - | - | - | - | - | |||
Jacob Bernard-Docker | Ice Dogs (DAY) | D | 23 | 2000-06-30 | No | 190 Lbs | 6 ft0 | No | No | N/A | No | No | 1 | Pro & Farm | 925,000$ | 925,000$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |||
Jasper Weatherby | Ice Dogs (DAY) | C | 25 | 1998-01-22 | No | 222 Lbs | 6 ft4 | No | No | N/A | No | No | 1 | Pro & Farm | 842,500$ | 842,500$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |||
Jay Bouwmeester | Ice Dogs (DAY) | D | 40 | 1983-09-27 | No | 206 Lbs | 6 ft4 | No | No | N/A | No | No | 2 | Pro & Farm | 3,250,000$ | 3,250,000$ | 0$ | 0$ | No | 3,250,000$ | - | - | - | - | - | - | - | - | No | - | - | - | - | - | - | - | - | |||
Jayce Hawryluk | Ice Dogs (DAY) | C | 27 | 1996-01-01 | No | 196 Lbs | 5 ft11 | No | No | N/A | No | No | 5 | Pro & Farm | 750,000$ | 750,000$ | 0$ | 0$ | No | 750,000$ | 750,000$ | 750,000$ | 750,000$ | - | - | - | - | - | No | No | No | No | - | - | - | - | - | |||
Joseph Woll | Ice Dogs (DAY) | G | 25 | 1998-07-12 | No | 203 Lbs | 6 ft3 | No | No | N/A | No | No | 2 | Pro & Farm | 750,000$ | 750,000$ | 0$ | 0$ | No | 750,000$ | - | - | - | - | - | - | - | - | No | - | - | - | - | - | - | - | - | |||
Kole Sherwood | Ice Dogs (DAY) | RW | 26 | 1997-01-22 | No | 212 Lbs | 6 ft1 | No | No | N/A | No | No | 1 | Pro & Farm | 735,000$ | 735,000$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |||
Lane Pederson | Ice Dogs (DAY) | C | 26 | 1997-08-04 | No | 192 Lbs | 6 ft0 | No | No | N/A | No | No | 1 | Pro & Farm | 735,000$ | 735,000$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |||
Mac Hollowell | Ice Dogs (DAY) | D | 25 | 1998-09-26 | Yes | 170 Lbs | 5 ft9 | No | No | N/A | No | No | 2 | Pro & Farm | 750,000$ | 750,000$ | 0$ | 0$ | No | 750,000$ | - | - | - | - | - | - | - | - | No | - | - | - | - | - | - | - | - | |||
Markus Granlund | Ice Dogs (DAY) | RW | 30 | 1993-04-16 | No | 180 Lbs | 6 ft0 | No | No | N/A | No | No | 2 | Pro & Farm | 1,300,000$ | 1,300,000$ | 0$ | 0$ | No | 1,300,000$ | - | - | - | - | - | - | - | - | No | - | - | - | - | - | - | - | - | |||
Markus Hannikainen | Ice Dogs (DAY) | LW | 30 | 1993-03-26 | No | 200 Lbs | 6 ft1 | No | No | N/A | No | No | 2 | Pro & Farm | 750,000$ | 750,000$ | 0$ | 0$ | No | 750,000$ | - | - | - | - | - | - | - | - | No | - | - | - | - | - | - | - | - | |||
Mikhail Grigorenko | Ice Dogs (DAY) | RW | 29 | 1994-05-16 | No | 206 Lbs | 6 ft3 | No | No | N/A | No | No | 3 | Pro & Farm | 1,200,000$ | 1,200,000$ | 0$ | 0$ | No | 1,200,000$ | 1,200,000$ | - | - | - | - | - | - | - | No | No | - | - | - | - | - | - | - | |||
Nelson Nogier | Ice Dogs (DAY) | D | 27 | 1996-01-01 | No | 191 Lbs | 6 ft2 | No | No | N/A | No | No | 5 | Pro & Farm | 750,000$ | 750,000$ | 0$ | 0$ | No | 750,000$ | 750,000$ | 750,000$ | 750,000$ | - | - | - | - | - | No | No | No | No | - | - | - | - | - | |||
Niklas Hjalmarsson | Ice Dogs (DAY) | D | 36 | 1987-06-06 | No | 197 Lbs | 6 ft3 | No | No | N/A | No | No | 2 | Pro & Farm | 6,000,000$ | 6,000,000$ | 0$ | 0$ | No | 6,000,000$ | - | - | - | - | - | - | - | - | No | - | - | - | - | - | - | - | - | |||
Paul Byron | Ice Dogs (DAY) | LW | 34 | 1989-04-27 | No | 158 Lbs | 5 ft9 | No | No | N/A | No | No | 2 | Pro & Farm | 4,000,000$ | 4,000,000$ | 0$ | 0$ | No | 4,000,000$ | - | - | - | - | - | - | - | - | No | - | - | - | - | - | - | - | - | |||
Ronnie Attard | Ice Dogs (DAY) | D | 24 | 1999-03-20 | No | 208 Lbs | 6 ft3 | No | No | N/A | No | No | 1 | Pro & Farm | 842,500$ | 842,500$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |||
Ryan Murphy | Ice Dogs (DAY) | D | 30 | 1993-03-31 | No | 185 Lbs | 5 ft11 | No | No | N/A | No | No | 2 | Pro & Farm | 825,000$ | 825,000$ | 0$ | 0$ | No | 825,000$ | - | - | - | - | - | - | - | - | No | - | - | - | - | - | - | - | - | |||
Sean Malone | Ice Dogs (DAY) | C | 28 | 1995-01-01 | No | 197 Lbs | 6 ft0 | No | No | N/A | No | No | 4 | Pro & Farm | 750,000$ | 750,000$ | 0$ | 0$ | No | 750,000$ | 750,000$ | 750,000$ | - | - | - | - | - | - | No | No | No | - | - | - | - | - | - | |||
Slater Koekkoek | Ice Dogs (DAY) | D | 29 | 1994-02-18 | No | 193 Lbs | 6 ft2 | No | No | N/A | No | No | 3 | Pro & Farm | 850,000$ | 850,000$ | 0$ | 0$ | No | 850,000$ | 850,000$ | - | - | - | - | - | - | - | No | No | - | - | - | - | - | - | - | |||
Zachary Senyshyn | Ice Dogs (DAY) | LW | 26 | 1997-03-30 | No | 205 Lbs | 6 ft1 | No | No | N/A | No | No | 1 | Pro & Farm | 700,000$ | 700,000$ | 0$ | 0$ | No | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
Total Players | Average Age | Average Weight | Average Height | Average Contract | Average Year 1 Salary |
---|---|---|---|---|---|
26 | 28.77 | 195 Lbs | 6 ft1 | 2.38 | 1,478,750$ |
5 vs 5 Forward | |||||||
---|---|---|---|---|---|---|---|
Line # | Left Wing | Center | Right Wing | Time % | PHY | DF | OF |
1 | Markus Granlund | 34 | 1 | 2 | 2 | ||
2 | 30 | 1 | 2 | 2 | |||
3 | Lane Pederson | 26 | 1 | 2 | 2 | ||
4 | Markus Hannikainen | 10 | 1 | 2 | 2 |
5 vs 5 Defense | |||||||
---|---|---|---|---|---|---|---|
Line # | Defense | Defense | Time % | PHY | DF | OF | |
1 | 34 | 1 | 2 | 2 | |||
2 | 30 | 1 | 2 | 2 | |||
3 | 26 | 1 | 2 | 2 | |||
4 | Aaron Ness | 10 | 1 | 2 | 2 |
Power Play Forward | |||||||
---|---|---|---|---|---|---|---|
Line # | Left Wing | Center | Right Wing | Time % | PHY | DF | OF |
1 | Markus Granlund | 51 | 1 | 2 | 2 | ||
2 | 49 | 1 | 2 | 2 |
Power Play Defense | |||||||
---|---|---|---|---|---|---|---|
Line # | Defense | Defense | Time % | PHY | DF | OF | |
1 | 51 | 1 | 2 | 2 | |||
2 | 49 | 1 | 2 | 2 |
Penalty Kill 4 Players Forward | ||||||
---|---|---|---|---|---|---|
Line # | Center | Wing | Time % | PHY | DF | OF |
1 | 51 | 1 | 2 | 2 | ||
2 | Markus Granlund | 49 | 1 | 2 | 2 |
Penalty Kill 4 Players Defense | ||||||
---|---|---|---|---|---|---|
Line # | Defense | Defense | Time % | PHY | DF | OF |
1 | 51 | 1 | 2 | 2 | ||
2 | 49 | 1 | 2 | 2 |
Penalty Kill 3 Players | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Line # | Wing | Time % | PHY | DF | OF | Defense | Defense | Time % | PHY | DF | OF |
1 | 51 | 1 | 2 | 2 | 51 | 1 | 2 | 2 | |||
2 | 49 | 1 | 2 | 2 | 49 | 1 | 2 | 2 |
4 vs 4 Forward | ||||||
---|---|---|---|---|---|---|
Line # | Center | Wing | Time % | PHY | DF | OF |
1 | 51 | 1 | 2 | 2 | ||
2 | Markus Granlund | 49 | 1 | 2 | 2 |
4 vs 4 Defense | ||||||
---|---|---|---|---|---|---|
Line # | Defense | Defense | Time % | PHY | DF | OF |
1 | 51 | 1 | 2 | 2 | ||
2 | 49 | 1 | 2 | 2 |
Last Minutes Offensive | ||||
---|---|---|---|---|
Left Wing | Center | Right Wing | Defense | Defense |
Markus Granlund |
Last Minutes Defensive | ||||
---|---|---|---|---|
Left Wing | Center | Right Wing | Defense | Defense |
Markus Granlund |
Extra Forwards | ||
---|---|---|
Normal | PowerPlay | Penalty Kill |
, , Lane Pederson | , | Lane Pederson |
Extra Defensemen | ||
---|---|---|
Normal | PowerPlay | Penalty Kill |
Jacob Bernard-Docker, Ryan Murphy, | Jacob Bernard-Docker | Ryan Murphy, |
Penalty Shots |
---|
, , Markus Granlund, , Lane Pederson |
Goalie |
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#1 : , #2 : |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Overall | Home | Visitor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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# | VS Team | GP | W | L | T | OTW | OTL | SOW | SOL | GF | GA | Diff | GP | W | L | T | OTW | OTL | SOW | SOL | GF | GA | Diff | GP | W | L | T | OTW | OTL | SOW | SOL | GF | GA | Diff | P | PCT | G | A | TP | SO | EG | GP1 | GP2 | GP3 | GP4 | SHF | SH1 | SP2 | SP3 | SP4 | SHA | SHB | Pim | Hit | PPA | PPG | PP% | PKA | PK GA | PK% | PK GF | W OF FO | T OF FO | OF FO% | W DF FO | T DF FO | DF FO% | W NT FO | T NT FO | NT FO% | PZ DF | PZ OF | PZ NT | PC DF | PC OF | PC NT |
Total | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.000 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0% | 0 | 0 | 0% | 0 | 0 | 0 | 0% | 0 | 0 | 0% | 0 | 0 | 0% | 0 | 0 | 0 | 0 | 0 | 0 |
Total For Players | ||||||||||||
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Games Played | Points | Streak | Goals | Assists | Points | Shots For | Shots Against | Shots Blocked | Penalty Minutes | Hits | Empty Net Goals | Shutouts |
0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
All Games | ||||||||
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GP | W | L | OTW | OTL | SOW | SOL | GF | GA |
0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Home Games | ||||||||
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GP | W | L | OTW | OTL | SOW | SOL | GF | GA |
0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Visitor Games | ||||||||
---|---|---|---|---|---|---|---|---|
GP | W | L | OTW | OTL | SOW | SOL | GF | GA |
0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Last 10 Games | |||||
---|---|---|---|---|---|
W | L | OTW | OTL | SOW | SOL |
0 | 0 | 0 | 0 | 0 | 0 |
Power Play Attemps | Power Play Goals | Power Play % | Penalty Kill Attemps | Penalty Kill Goals Against | Penalty Kill % | Penalty Kill Goals For |
---|---|---|---|---|---|---|
0 | 0 | 0% | 0 | 0 | 0% | 0 |
Shots 1 Period | Shots 2 Period | Shots 3 Period | Shots 4+ Period | Goals 1 Period | Goals 2 Period | Goals 3 Period | Goals 4+ Period |
---|---|---|---|---|---|---|---|
0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Face Offs | ||||||||
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Won Offensive Zone | Total Offensive | Won Offensive % | Won Defensif Zone | Total Defensive | Won Defensive % | Won Neutral Zone | Total Neutral | Won Neutral % |
0 | 0 | 0% | 0 | 0 | 0% | 0 | 0 | 0% |
Puck Time | |||||
---|---|---|---|---|---|
In Offensive Zone | Control In Offensive Zone | In Defensive Zone | Control In Defensive Zone | In Neutral Zone | Control In Neutral Zone |
0 | 0 | 0 | 0 | 0 | 0 |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Day | Game | Visitor Team | Score | Home Team | Score | ST | OT | SO | RI | Link |
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Arena Capacity - Ticket Price Attendance - % | ||
---|---|---|
Level 1 | Level 2 | |
Capacity | 2000 | 1000 |
Ticket Price | 35 | 0 |
Attendance | 0% | 0% |
Attendance PCT | 0% | 0% |
Income | |||||
---|---|---|---|---|---|
Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Capacity | Team Popularity | 0 | 0 - 0% | 0$ | 0$ | 3000 | 100 |
Expenses | |||
---|---|---|---|
Year To Date Expenses | Players Total Salaries | Players Total Average Salaries | Coaches Salaries |
0$ | 0$ | 0$ | 0$ |
Salary Cap Per Days | Salary Cap To Date | Players In Salary Cap | Players Out of Salary Cap |
---|---|---|---|
0$ | 0$ | 0 | 0 |
Estimate | |||
---|---|---|---|
Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
0$ | 0 | 0$ | 0$ |
# | Player Name | GP | G | A | P | +/- | PIM | HIT | HTT | SHT | SHT% | SB | MP | AMG | PPG | PPA | PPP | PPS | PKG | PKA | PKP | PKS | GW | GT | FO% | HT | P/20 | PSG | PSS |
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# | Goalie Name | GP | W | L | OTL | PCT | GAA | MP | PIM | SO | GA | SA | SAR | A | EG | PS % | PSA |
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Overall | Home | Visitor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Year | GP | W | L | T | OTW | OTL | SOW | SOL | GF | GA | Diff | GP | W | L | T | OTW | OTL | SOW | SOL | GF | GA | Diff | GP | W | L | T | OTW | OTL | SOW | SOL | GF | GA | Diff | P | G | A | TP | SO | EG | GP1 | GP2 | GP3 | GP4 | SHF | SH1 | SP2 | SP3 | SP4 | SHA | SHB | Pim | Hit | PPA | PPG | PP% | PKA | PK GA | PK% | PK GF | W OF FO | T OF FO | OF FO% | W DF FO | T DF FO | DF FO% | W NT FO | T NT FO | NT FO% | PZ DF | PZ OF | PZ NT | PC DF | PC OF | PC NT |
# | Player Name | GP | G | A | P | +/- | PIM | HIT | HTT | SHT | SHT% | SB | MP | AMG | PPG | PPA | PPP | PPS | PKG | PKA | PKP | PKS | GW | GT | FO% | HT | P/20 | PSG | PSS |
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# | Goalie Name | GP | W | L | OTL | PCT | GAA | MP | PIM | SO | GA | SA | SAR | A | EG | PS % | PSA |
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